IMU-aided Affine-photometric KLT Feature Tracker in CUDA Framework

by Jun-Sik Kim

This library implements the KLT Tracking algorithm with 8-DOF affine-photometric motion model. The tracking can be assisted by a synchronized IMU for better performance. This implementation is written in NVIDIA CUDA framework for parallel processing.

The CUDA-based tracker is interfaced with the class CFeature2DPool. Although neither the IPP nor OpenCV libraries are used in our CUDA implementation, this interface class requires both of them in order to handle images.

CUDA implementation

Our KLT-GPU code is implemented in following two cu files:

cuda_convolutionSeparable_kernel.cu:
image smoothing, available in the CUDA samples